Abstract
With the expansion of the scale of higher education in my country, the employment situation of college students is becoming increasingly severe. The basic way to improve the employment situation and the quality of employment is to further improve the quality of personnel training. In the context of the era of big data, my country’s college teaching has also made some reforms in response to the current era of big data. The purpose of this article is to study the impact of professional talent training in colleges and universities on student employment and school quality in the era of big data. Therefore, this article takes the university undergraduate talent training model as the comparative research object, and uses literature research, questionnaire method, comparative analysis, mathematical statistics and other methods to grasp the current situation, similarities and differences of the undergraduate talent training model in ordinary universities under the background of big data. The advantages and disadvantages of the current university teaching model under the background of big data, taking the current situation of university professional education reform as the starting point, through the inevitable discussion that the application of modern education technology is inevitable to deepen the university professional education reform, it is proposed to apply modern education technology to deepen the university Several countermeasures and suggestions for professional education reform. Experimental research results show that, in the context of the rapid development of this big data era, the popularization and improvement of college education also needs to open up new ideas to innovate, and it also requires every teacher and student to actively think and challenge.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.